Cytometry plays an indispensable role in many medical and research fields. Image-based and flow cytometers have found widespread use in these fields for counting cells and measuring their physical and molecular characteristics, e.g. Shapiro, Practical Flow Cytometry, 4th Edition (Wiley-Liss, 2003). In particular, flow cytometry is a powerful technique for rapidly measuring multiple parameters on large numbers of individual cells of a population enabling acquisition of statistically reliable information about the population and its subpopulations. The technique has been important in the detection and management of a range of diseases, particularly blood-related diseases, such as hematopoietic cancers, HIV, and the like, e.g. Woijciech, Flow Cytometry in Neoplastic Hematology, Second Edition (Informa Healthcare, 2010); Brown et al, Clinical Chemistry, 46: 8(B); 1221-1229 (2000). Despite this utility, flow cytometry has a number of drawbacks, including limited sensitivity in rare cell detection, e.g. Campana et al, Hematol. Oncol. Clin. North Am., 23(5):1083-1098 (2009); limitations in the number of cell parameters that can be practically measured at the same time; and costly instrumentation.
In view of the above, it would be advantageous to many medical and research fields if there were available alternative methods and systems for making multiparameter measurements on large numbers of individual cells that overcame the drawbacks of current cytometric approaches.